We have to predict whether a customer will respond to a Personal Loan Campaign!
Jupyter Notebook
Personal-Loan-Modelling
Data Description:
The file Bank_Personal_Loan_Modelling.csv contains data on 5000 customers. The data include customer demographic information (age, income, etc.), the customer's relationship with the bank (mortgage, securities account, etc.), and the customer response to the last personal loan campaign (Personal Loan). Among these 5000 customers, only 480 (= 9.6%) accepted the personal loan that was offered to them in the earlier campaign.
Attribute Information:
ID : Customer ID
Age : Customer's age in completed years
Experience : No. of years of professional experience
Income : Annual income of the customer ($ 000)
ZIP Code : Home Address Zip Code
Family : Family size of the customer
CCAvg : Avg. Spending on Credit Card per Month ($ 000)